Analyzing Unstructured Data with GraphDB 9.8

Demonstration of how to use text analysis to populate knowledge graphs from unstructured documents and synchronize downstream systems via Kafka.

This webinar is recorded and available on YouTube.


Enterprise Knowledge Graphs bring together and harmonize all-important organizational knowledge and metadata. They focus on business-specific information needs and how to properly source the needed data rather than to analyze preexisting application models. A key challenge in sourcing the knowledge is to analyze unstructured data. A recent cross-industry study uncovered that on average less than 1% of unstructured data is analyzed or used at all, despite that the majority of internal business processes are organized around documents.

The main focus of this webinar is to demonstrate the new features in GraphDB 9.8 enabling the users to connect text mining technology with knowledge graphs. We show practical examples of how to:

  • Register external text mining services based on GATE, Spacy and Ontotext annotation services;
  • Transform external annotation models into RDF using SPARQL queries;
  • Extend the out-of-the-box supported services with any third party service like Refinitiv;
  • Subscribe for specific patterns of graph changes over Kafka Connector.

All these features are available in the latest GraphDB 9.8 Free, Standard or Enterprise.

Who is this webinar for:

  • Users who need to analyze or populate KGs from unstructured documents;
  • Data scientists who need to use the power of graph to disambiguate entities;
  • Data engineers who need to implement text mining workflows and persist their output into knowledge graphs.

Expected duration:

  • 45 minutes presentation
  • 15 minutes Q&A session

About The Speaker

Vassil Momtchev

Vassil Momtchev

CTO, Ontotext

Vassil has more than 15 years in software development in various domains like life sciences, pharmaceutical, health care and telecommunication. In the past 10 years he’s mostly engaged with the development of complex enterprise knowledge management solutions that features natural language processing, text analytics, reasoning, semantics, ontology design, linked data, conceptual model design, implementation of formal grammars and graph databases.

Ivaylo Kabakov

Ivaylo Kabakov

Head of Semantic Analytics Solutions, Ontotext

Ivaylo Kabakov is the head of Semantic Analytics Solutions team at Ontotext. His pursuit of interesting challenges brought him to Ontotext, where his passion for making computers do fascinating things met with the cutting-edge developments in semantic technologies. Ivaylo’s involvement with the company has guided him through the full stack of duties for delivering solutions to clients. His strive has always been for adding practical value while doing it with a pedantic focus on quality.